Go

While watching Mitchell Hashimoto’s excellent talk1 on Go testing, I came across this neat technique for deferring teardown to the caller. Let’s say you have a helper function in a test that needs to perform some cleanup afterward. You can’t run the teardown inside the helper itself because the test still needs the setup. For example, in the following case, the helper runs its teardown immediately: func TestFoo(t *testing.T) { helper(t) // Test logic here: resources may already be cleaned up! } func helper(t *testing.T) { t.Helper() // Setup code here. // Teardown code here. defer func() { // Clean up something. }() } When helper is called, it defers its teardown—which executes at the end of the helper function, not the test. But the test logic still depends on whatever the helper set up. So this approach doesn’t work. ...

There are primarily three ways of sorting slices in Go. Early on, we had the verbose but flexible method of implementing sort.Interface to sort the elements in a slice. Later, Go 1.8 introduced sort.Slice to reduce boilerplate with inline comparison functions. Most recently, Go 1.21 brought generic sorting via the slices package, which offers a concise syntax and compile-time type safety. These days, I mostly use the generic sorting syntax, but I wanted to document all three approaches for posterity. ...

Comparing interface values in Go has caught me off guard a few times, especially with nils. Often, I’d expect a comparison to evaluate to true but got false instead. Many moons ago, Russ Cox wrote a fantastic blog post1 on interface internals that clarified my confusion. This post is a distillation of my exploration of interfaces and nil comparisons. Interface internals Roughly speaking, an interface in Go has three components: ...

Middleware is usually the go-to pattern in Go HTTP servers for tweaking request behavior. Typically, you wrap your base handler with layers of middleware—one might log every request, while another intercepts specific routes like /special to serve a custom response. However, I often find the indirections introduced by this pattern a bit hard to read and debug. I recently came across the embedded delegation pattern while browsing the Gin1 repo. Here, I explore both patterns and explain why I usually start with delegation whenever I need to modify HTTP requests in my Go services. ...

I’ve always found the signature of io.Reader a bit odd: type Reader interface { Read(p []byte) (n int, err error) } Why take a byte slice and write data into it? Wouldn’t it be simpler to create the slice inside Read, load the data, and return it instead? // Hypothetical; what I *thought* it should be Read() (p []byte, err error) This felt more intuitive to me—you call Read, and it gives you a slice filled with data, no need to pass anything. ...

Just like any other dynamically growable container structure, Go slices come with a few gotchas. I don’t always remember all the rules I need to be aware of. So this is an attempt to list some of the most common mistakes I’ve made at least once. Slices are views over arrays In Go, a slice is a lightweight wrapper around an array. Instead of storing data itself, it keeps track of three things: a pointer to an underlying array where the data is stored, the number of elements it currently holds, and the total capacity before it needs more space. The Go runtime defines it like this: ...

People love single-method interfaces (SMIs) in Go. They’re simple to implement and easy to reason about. The standard library is packed with SMIs like io.Reader, io.Writer, io.Closer, io.Seeker, and more. One cool thing about SMIs is that you don’t always need to create a full-blown struct with a method to satisfy the interface. You can define a function type, attach the interface method to it, and use it right away. This approach works well when there’s no state to maintain, so the extra struct becomes unnecessary. However, I find the syntax for this a bit abstruce. So, I’m jotting down a few examples here to reference later. ...

I was fiddling with graphlib in the Python stdlib and found it quite nifty. It processes a Directed Acyclic Graph (DAG), where tasks (nodes) are connected by directed edges (dependencies), and returns the correct execution order. The “acyclic” part ensures no circular dependencies. Topological sorting is useful for arranging tasks so that each one follows its dependencies. It’s widely used in scheduling, build systems, dependency resolution, and database migrations. For example, consider these tasks: ...

Besides retries, circuit breakers1 are probably one of the most commonly employed resilience patterns in distributed systems. While writing a retry routine is pretty simple, implementing a circuit breaker needs a little bit of work. I realized that I usually just go for off-the-shelf libraries for circuit breaking and haven’t written one from scratch before. So, this is an attempt to create a sloppy one in Go. I picked Go instead of Python because I didn’t want to deal with sync-async idiosyncrasies or abstract things away under a soup of decorators. ...

Ever since Rob Pike published the text on the functional options pattern1, there’s been no shortage of blogs, talks, or comments on how it improves or obfuscates configuration ergonomics. While the necessity of such a pattern is quite evident in a language that lacks default arguments in functions, more often than not, it needlessly complicates things. The situation gets worse if you have to maintain a public API where multiple configurations are controlled in this manner. ...

These days, I don’t build hierarchical types through inheritance even when writing languages that support it. Type composition has replaced almost all of my use cases where I would’ve reached for inheritance before. I’ve written1 about how to escape the template pattern2 hellscape and replace that with strategy pattern3 in Python before. While by default, Go saves you from shooting yourself in the foot by disallowing inheritance, it wasn’t obvious to me how I could apply the strategy pattern to make things more composable and testable. ...

While I like Go’s approach of treating errors as values as much as the next person, it inevitably leads to a situation where there isn’t a one-size-fits-all strategy for error handling like in Python or JavaScript. The usual way of dealing with errors entails returning error values from the bottom of the call chain and then handling them at the top. But it’s not universal since there are cases where you might want to handle errors as early as possible and fail catastrophically. Yet, it’s common enough that we can use it as the base of our conversation. ...

I used reach for reflection whenever I needed a Retry function in Go. It’s fun to write, but gets messy quite quickly. Here’s a rudimentary Retry function that does the following: It takes in another function that accepts arbitrary arguments. Then tries to execute the wrapped function. If the wrapped function returns an error after execution, Retry attempts to run the underlying function n times with some backoff. The following implementation leverages the reflect module to achieve the above goals. We’re intentionally avoiding complex retry logic for brevity: ...

Despite moonlighting as a gopher for a while, the syntax for type assertion and type switches still trips me up every time I need to go for one of them. So, to avoid digging through the docs or crafting stodgy LLM prompts multiple times, I decided to jot this down in a gobyexample1 style for the next run. Type assertion Type assertion in Go allows you to access an interface variable’s underlying concrete type. After a successful assertion, the variable of interface type is converted to the concrete type to which it’s asserted. ...

As of now, unlike Python or NodeJS, Go doesn’t allow you to specify your development dependencies separately from those of the application. However, I like to specify the dev dependencies explicitly for better reproducibility. While working on a new CLI tool1 for checking dead URLs in Markdown files, I came across this neat convention: you can specify dev dependencies in a tools.go file and then exclude them while building the binary using a build tag. ...

I needed to integrate rate limiting into a relatively small service that complements a monolith I was working on. My initial thought was to apply it at the application layer, as it seemed to be the simplest route. Plus, I didn’t want to muck around with load balancer configurations, and there’s no shortage of libraries that allow me to do this quickly in the app. However, this turned out to be a bad idea. In the event of a DDoS1 or thundering herd2 incident, even if the app rejects the influx of inbound requests, the app server workers still have to do a minimal amount of work. ...

I’ve always had a thing for old-school web tech. By the time I joined the digital fray, CGI scripts were pretty much relics, but the term kept popping up in tech forums and discussions like ghosts from the past. So, I got curious, started reading about them, and wanted to see if I could reason about them from the first principles. Writing one from the ground up with nothing but Go’s standard library seemed like a good idea. ...

Suppose, you have a function that takes an option struct and a message as input. Then it stylizes the message according to the option fields and prints it. What’s the most sensible API you can offer for users to configure your function? Observe: // app/src package src // Option struct type Style struct { Fg string // ANSI escape codes for foreground color Bg string // Background color } // Display the message according to Style func Display(s *Style, msg string) {} In the src package, the function Display takes a pointer to a Style instance and a msg string as parameters. Then it decorates the msg and prints it according to the style specified in the option struct. In the wild, I’ve seen 3 main ways to write APIs that let users configure options: ...

I was curious to see if I could prototype a simple load balancer in a single Go script. Go’s standard library and goroutines make this trivial. Here’s what the script needs to do: Spin up two backend servers that’ll handle the incoming requests. Run a reverse proxy load balancer in the foreground. The load balancer will accept client connections and round-robin them to one of the backend servers; balancing the inbound load. Once a backend responds, the load balancer will relay the response back to the client. For simplicity, we’ll only handle client’s GET requests. Obviously, this won’t have SSL termination, advanced balancing algorithms, or session persistence like you’d get with Nginx1 or Caddy2. The point is to understand the basic workflow and show how Go makes it easy to write this sort of stuff. ...

I was cobbling together a long-running Go script to send webhook messages to a system when some events occur. The initial script would continuously poll a Kafka topic for events and spawn new goroutines to make HTTP requests to the destination. This had two problems: It could create unlimited goroutines if many events arrived quickly It might overload the destination system by making many concurrent requests In Python, I’d use just asyncio.Semaphore to limit concurrency. I’ve previously written about this here1. Turns out, in Go, you could do the same with a buffered channel. Here’s how the naive version looks: ...